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Developing an impact-based combined drought index for monitoring crop yield anomalies in the Upper Blue Nile Basin, Ethiopia Preview this item
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Developing an impact-based combined drought index for monitoring crop yield anomalies in the Upper Blue Nile Basin, Ethiopia

Author: Yared Ashenafi Bayissa
Publisher: [Place of publication not identified] CRC Press, 2018.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Having a robust drought monitoring system for Ethiopia is crucial to mitigate the adverse impacts of droughts. Yet, such monitoring system still lacks in Ethiopia, and in the Upper Blue Nile (UBN) basin in particular. Several drought indices exist to monitor drought, however, these indices are unable, individually, to provide concise information on the occurrence of meteorological, agricultural and hydrological  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
(OCoLC)1046463381
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Yared Ashenafi Bayissa
ISBN: 9780429679773 0429679777 9780429399510 0429399510 9780429679766 0429679769 9780429679759 0429679750
OCLC Number: 1061045936
Description: 1 online resource
Contents: Cover; Title Page; Copyright Page; Table of contents; Acknowledgements; Dedication; Summary; List of symbols; List of acronyms; 1: Introduction; 1.1 Background; 1.2 Drought monitoring; 1.3 Problem statement; 1.4 Research objectives; 1.5 Main steps in research methodology; 1.6 Research significance and innovation; 1.6.1 Research significance; 1.6.2 Innovation; 1.7 Description of the study area; 1.8 Dissertation structure; 2: Spatio-temporal assessment of meteorological drought under the influence of varying record length; 2.1 Introduction; 2.2 Stations selection and data analysis 2.3 Selection of the Probability Distribution Function (PDF) for the Standardized Precipitation Index (SPI)2.4 Methodology of experiments; 2.5 Results and discussion; 2.5.1 Effect of record length on drought analysis; 2.5.2 Temporal assessment, and trend analysis of drought; 2.5.3 Areal extent of drought; 2.5.4 Spatio-temporal analysis to assess the spatial variability of drought frequency; 2.6 Conclusion; 3: Comparison of the performance of six drought indices in assessing and characterising historic drought events; 3.1 Introduction; 3.2 Data; 3.2.1 Historical drought events 3.2.2 Actual evapotranspiration (ET) and soil moisture data3.2.3 Rainfall and temperature data; 3.2.4 River discharge data; 3.3 Drought indicators; 3.3.1 Meteorological drought indicators; 3.3.2 Agricultural drought indicators; 3.3.3 Hydrological drought indicator; 3.3.4 Aggregate Drought Index (ADI); 3.4 Methods; 3.4.1 Correlation between drought indices; 3.4.2 Comparison of drought indices based on drought onset, duration, and severity; 3.5 Results and discussion; 3.5.1 Time series of the drought indices; 3.5.2 Correlation between drought indices 3.5.3 Comparison of drought indices based on drought characteristics3.5.4 Comparison of drought indices through characterizing the historic drought events; 3.6 Conclusion; 4: Developing a combined drought index and prediction model to monitor drought-related crop yield reduction; 4.1 Introduction; 4.2 Data; 4.3 Methods; 4.3.1 Detrending the crop yield data; 4.3.2 Correlation analysis of crop yield with drought index; 4.3.3 Qualitative analysis of crop yield and drought index values; 4.3.4 Principal Component Analysis (PCA) based CDI; 4.3.5 Impact-based CDI 4.3.6 Prediction model of crop-yield anomalies4.4 Results and discussion; 4.4.1 Correlation analysis of the individual drought indices with crop-yield anomalies; 4.4.2 Comparison of drought indices with crop yield anomalies; 4.4.3 Combined drought index developed using Principal Component Analysis (PCA); 4.4.4 Combined drought index developed using an impact-based optimal CDI relative weights; 4.4.5 Predicion models of crop yield anomalies; 4.5 Conclusions; 5: Application of Earth observation data for developing a combined drought index and crop yield prediction model; 5.1 Introduction
Responsibility: by Uared Ashenafi Bayissa.

Abstract:

Having a robust drought monitoring system for Ethiopia is crucial to mitigate the adverse impacts of droughts. Yet, such monitoring system still lacks in Ethiopia, and in the Upper Blue Nile (UBN) basin in particular. Several drought indices exist to monitor drought, however, these indices are unable, individually, to provide concise information on the occurrence of meteorological, agricultural and hydrological droughts. A combined drought index (CDI) using several meteorological, agricultural and hydrological drought indices can indicate the occurrence of all drought types, and can provide information that facilitates the drought management decision-making process. This thesis proposes an impact-based combined drought index (CDI) and a regression prediction model of crop yield anomalies for the UBN basin. The impact-based CDI is defined as a drought index that optimally combines the information embedded in other drought indices for monitoring a certain impact of drought, i.e. crop yield for the UBN. The developed CDI and the regression model have shown to be effective in indicating historic drought events in UBN basin. The impact-based CDI could potentially be used in the future development of drought monitoring in the UBN basin and support decision making in order to mitigate adverse drought impacts.

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